The Transparency Market Research, a market research firm in the US, predicted in their formerly published report that the market value of the video surveillance hardware and video surveillance as a service (VSaaS) will reach 42.81 billion dollars in 2019 with a compound annual growth rate (CAGR) of 19.1%. The market value of the video surveillance hardware was 9.48 billion dollars in 2012. Its CAGR between 2013 and 1019 is expected to be 17.3%. The market share of closed-circuit televisions and their memories was 37% of the overall hardware market in 2012, occupying the largest proportion. The next largest market share, 32%, is the internet protocol camera (IP cam) having the cloud functionality. The report also predicted IP cam would be favored by more people in the coming years and will reach around 46% of market share in 2019. Closed-circuit televisions and their memories will gradually lose their market share. This trend shows that the mainstream of modern video surveillance technology is gradually turning to IP-based monitors. Users become accustomed to backupping the video taken by monitors in cloud hard disks progressively and manage the video contents via the cloud.
Nonetheless, as the amount of monitors that surveillance service providers or users need to manage becomes huge increasingly, it is extremely difficult to detect abnormal conditions in monitors real-timely. An efficient surveillance system is required for detecting abnormalities automatically. Accordingly, the present invention provides a distributed automatic notification method for abnormality in remote massive monitors for real-time surveillance on massive monitors using a distributed computing system. The principle is to use statistical tools for analyzing if monochromatic single-frame images appear in the continuous images converted from the data stream of the monitors in order to judge if abnormalities occur.
In addition, when the data stream is not available, namely, when the communication between the surveillance center and the monitors is disconnected, the present invention is designed to generate a disconnect prompt stream automatically. The appearance of monochromatic single-frame image while converting a disconnect prompt stream to continuous video is judged using statistical tools. Then the color of the monochromatic single-frame image is detected for determining the cause, whether a network disconnection or a monitor failure problem, of the monochromatic single-frame image.
Besides, the color of monochromatic single-frame image can be due to natural phenomena. For example, the color of the video taken by a monitor installed in an environment without lighting at night will be black monochromatically black after sunset. The present invention also provides exception configuration for specific monochromatic video color in specific video times for preventing false judgment.
The present invention is applicable to various monitors that edit video data using a real-time streaming format. It can process video of any resolution, detect network abnormality automatically and dynamically, and support dynamic event reminding and history analysis.